The replicative model of evolution: A general theory

I propose a mathematical model of cultural evolution to explain why false theories and meaning systems or maladaptive beliefs may spread and become fixed in a population while assuming that their diffusion rates are lower than their true counterparts. By combining ideas from judgment aggregation and the Condorcet Jury theorem with cultural evolution dynamics, I introduce a new epistemic stage in the cultural evolution process where culturally transmitted theories not only spread “horizontally” (across individuals in the same generation) and “vertically” (from one generation to the next), but also inside individual brains (“personal reflection process”). This occurs when a brain adopts a maladaptive theory (not received from outside) by means of internal inference from other false premise/idea that was indeed received culturally. In this context, false theories may favor the assumption of other false theories after the individuals have been exposed to true information about their logical connection, and increase their presence in the population within the normal and adaptive logical working of our brains. Using a simple stylized model and subsequent simulations I identify the parametric conditions in which false theories become universally accepted, so that the model could be tested empirically.

Abstract: In this paper I argue, first, that human lifeways depend on cognitive capital that has typically been built over many generations. This process of gradual accumulation produces an adaptive fit between human agents and their environments; an adaptive fit that is the result of hidden‐hand, evolutionary mechanisms. To explain distinctive features of human life, we need to understand how cultures evolve. Second, I distinguish a range of different evolutionary models of culture. Third, I argue that none of meme‐based models, dual inheritance models, nor Boyd and Richerson's models fully succeed in explaining this adaptive fit between agent and the world. I then briefly develop an alternative. Finally, I explore (in a preliminary way) constraints on cultural adaptation. The processes of cultural evolution sometimes built a fit between agents and their environment, but they do not always do so. Why is folk medicine, for example, so much less reliable than folk natural history?

Living systems, besides acquiring information ontologically, i.e., as an inherent part of their nature, have the special ability to constantly incorporate the available data on their environment through learning (cognition). Therefore, cognition is one of the basic properties that characterize living beings, since even lesser organisms display some kind of learning. This chapter shares the opinion that “humans are a cultural species,” because much of human behavior is determined by an information system acquired via social transmission. It is assumed that humans are characterized by the display of behaviors derived from information processing of three distinct natures: ontological, those acquired by individual experience, and those acquired by social transmission. It is recognized that culture can evolve following Darwinian assumptions, and that knowledge transmission is one of the elementary processes in cultural evolution and in the relation between people and their understanding of nature. This chapter now turns to the three bases description of human information, and then it turns its attention to social knowledge transfer from an evolutionary perspective. Finally, we discuss how information transmission has been analyzed by ethnobiological studies and how it can be used to understand the evolutionary dynamics of social-ecological systems, drawing upon standard ethnobiological works.

Recent theoretical work on the processes of cultural evolution helps to provide a clearer picture of the relationship between genetic and cultural influences on human behavior. The theory uses methods borrowed from evolutionary biology to study the unique properties of culture, but in a framework that permits a direct analysis of how genes and culture interact. The different scholars contributing to this program of research have rather different hypotheses regarding the relative importance of the processes that operate to cause cultural evolution. Some human sociobiologists propose that cultural evolution is very strongly constrained by the decision‐making of individuals. If so, human behavior can in principle be predicted rather directly from considerations of genetic fitness maximization. We are more impressed by the dynamic complexities introduced by a second system of inheritance. The difference between these hypotheses turns on the extent to which information is costly to acquire. When it is...

The question of how and why innovations spread through populations has been the focus of extensive research in various scientific disciplines over recent decades. Generally, innovation diffusion is defined as the process whereby a few members of a social system initially adopt an innovation, then over time more individuals adopt until all (or most) members have adopted the new idea (e.g. Rogers 2003; Ryan and Gross 1943; Valente 1993). Anthropologists and archaeologists have argued that this process is one of the most important processes in cultural evolution (Richerson et al. 1996) and much work has been devoted to describing and analysing the temporal and spatial patterns of the spread of novel techniques and ideas from a particular source to their present distributions. Classic case studies include the spread of agricultural inventions such as hybrid corn (e.g. Griliches 1957; Ryan and Gross 1943), the spread of historic gravestone motifs in New England (Dethlefsen and Deetz 1966; Scholnick 2012), and the spread of bow and arrow technology (Bettinger and Eerkins 1999). (For a more comprehensive list see Rogers and Shoemaker (1971) who reviewed 1,500 studies of innovation diffusion.) Interestingly, the temporal diffusion dynamic in almost all case studies is characterized by an S-shaped diffusion curve describing the fraction of the population which has adopted the innovation at a certain point in time. Similarly, the spatial dynamics tend to resemble travelling wave-like patterns (see Steele 2009 for examples). The basic puzzle posed by innovation diffusion is the observed lag between an innovation’s first appearance and its general acceptance within a population (Young 2009). In other words, what are the individual-level mechanisms that give rise to the observed population-level pattern? Again, scientific fields as diverse as economics/marketing science (e.g. Bass 1969; Van den Bulte and Stremersch 2004; Young 2009), geography (e.g. Hägerstrand 1967), or social science (e.g. Henrich 2001; Steele 2009; Valente 1996; Watts 2002) offer interesting insights into this question without reaching a consensus about the general nature of individual adoption decisions. In archaeological and anthropological applications, population-level patterns inferred from the archaeological record, such as adoption curves, are often the only direct evidence about past cultural traditions (Shennan 2011).

Previous articleNext article No AccessNew Biological BooksBehavior Pattern and Process in Cultural Evolution. Origins of Human Behavior and Culture, Volume 2. Edited by StephenShennan. Berkeley (California): University of California Press. $60.00. vii 341 p.; ill.; index. 9780520255999. 2009.R.LeeLymanR.LeeLymanAnthropology, University of Missouri, Columbia, Missouri Search for more articles by this author Anthropology, University of Missouri, Columbia, MissouriPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Quarterly Review of Biology Volume 84, Number 3September 2009 Published in association with Stony Brook University Article DOIhttps://doi.org/10.1086/644687 Views: 6Total views on this site 2009 by The University of Chicago Press. All rights reserved.PDF download Crossref reports no articles citing this article.

The process of cultural evolution

Archaeologists have long been aware that the Pithouse period, which occupies most of the 1st millennium A.C., established the village farming foundations for the subsequent Pueblo florescence in the southwestern United States. Nevertheless, we understand all too little of the organization of society during the Pithouse period, or of directions and processes of cultural evolution within the period. Stimulated by this situation, the present study interprets excavation data from a site of the late Pithouse period in the Hueco Bolson of western Texas. The study asks how household units were composed, how these units were distributed within the community, and how the composition and lay-out of the village reflects the organizational patterns of society during the Pithouse period. Some consideration is also given to the question of changes in social organization during Pithouse times, and between the Pithouse period and the succeeding Pueblo period.

Humans often set aside their own self-interest to help others and punish free riders, even when interacting with strangers. To explain the origin of these ‘broad-scope prosocial preferences’, we should consider the processes of cultural evolution that might have acted in early human populations. Two types of cultural selection can be distinguished: CS1, in which cultural differences between individuals cause differences in their reproductive success; and CS2, in which cultural differences between individuals cause differences in their ‘cultural fitness’. This chapter proposes, speculatively, that human social evolution involved a gradual decoupling of cultural fitness from reproductive success. A cultural version of Hamilton’s rule, in which the coefficient of genetic relatedness is replaced by a coefficient of cultural relatedness, provides a helpful organizing framework for thinking about the evolution of social behaviour by CS1, and leads to a ‘cultural relatedness hypothesis’ regarding the origins of human prosociality.

This paper summarizes, contrasts, and reviews recent accounts of cultural evolution in our species offered by Cecilia Heyes in Cognitive Gadgets, Kevin Laland in Darwin’s Unfinished Symphony, and Michael Tomasello in Becoming Human. Our critical discussion focuses on the authors’ accounts of social learning, and the relationship each hypothesizes between cultural evolutionary and biological evolutionary processes. We find that both Laland and Tomasello seek to explain cultural evolution in humans as reliant upon processes of joint attention and shared intentionality (the development of which is largely the focus of Tomasello’s book). Heyes’ account of social learning, in which no particular role is assigned to human intersubjectivity and the same basic associative learning mechanisms of nonsocial learning are also invoked to explain social learning, stands apart. As to the relation of cultural and biological evolution, Laland offers readers a thorough account of the two with detailed analyses of social learning across various non-primate species, and uniquely, among these authors, attends to the influence of genes on social learning. For his part, Tomasello provides readers with a richly detailed experimental accounting of human-unique forms of social learning using Great Apes as points of contrast.

This study provides an account of how a naturalistic orientation in epistemology known as evolutionary epistemology can benefit from integration with some more recent advancements in cultural evolutionary theory. In particular, this thesis explores the ways in which a Darwinian selective framework of culture provides new insights to rethink unsolved epistemological disputes and problems such as the growth of scientific ideas, the notion of scientific progress, the ‘context distinction’, the theory ladenness of science and a demarcation criterion between science and other cultural realms. All these issues are approached from an evolutionary and selective standpoint that assumes that biological and cultural selection are representative of a wider and more encompassing selective process. Thus, the thesis also explores theoretical disputes concerning the analogies and disanalogies between cultural and biological selection. Five early evolutionary analogies of knowledge accretion are explored in the first chapter setting the context of the debate for the epistemological issues that are connected in the other chapters to cultural evolution. Here, a populationist account of scientific ideas is presented as a viable model to study the conceptual and ‘ideational’ dynamics of change in science. In the last part of this work, my populationist and selective model is applied to study a specific scientific innovation: a molecular technique for taxonomic identification and classification known as DNA barcoding. Finally, the last chapter explores the use of text analysis to investigate the network of concepts and ideas that relate to the ‘DNA barcoding’ concept’. Here, I evaluate the impact of this technique on the fields of taxonomy/systematics, particularly, for what concerns the so called ‘species problem’.

Within the field of cultural evolution, particular attention has been devoted to the process of cumulative cultural evolution (CCE). Much of modern human behaviour is believed to be attributable to CCE. Despite common consensus over the importance of this topic, there are disparities in how the term has been defined and interpreted (and correspondingly the breadth of phenomena it is considered to encompass). Defined broadly, CCE refers to processes of cultural change involving alterations in cultural traits occurring over multiple episodes of social transmission, but there is variation in the additional criteria considered to be defining features. This chapter will highlight points of contention by examining some key borderline cases, which illustrate how the preferred definition of CCE impacts its presumed scope (e.g. whether it is restricted to humans). It is likely that differing motivations for interest in CCE underpin some of the differences in characterization of the process.

This paper discusses the role of interactional and cognitive mechanisms in the emergence of (proto)linguistic structures and the evolution of (proto)language(s). Both the social, interactive nature of human communication and the interactional timescale have received increasing attention in investigations of how structure emerges in language. This has also led to an increasing focus on the mechanisms involved in the dialogic co-construction of structure and meaning in interaction. These include ad hoc constructionalization, interactive alignment, conceptual pacts, reuse and modification, and local forms of entrenchment, routinisation and schematisation. Interactional and cognitive mechanisms like these do not only play a crucial role in the emergence of structure in modern languages. They can also help explain how the first (proto)constructions came into being in hominin interaction. Frequently re-occuring, temporary, local (proto)constructions acquired increasing degrees of entrenchment, which led to their subsequent diffusion throughout hominin communities. They were then subject to processes of conventionalisation and cumulative cultural evolution. This process is hypothesised to eventually have led to the gradual transition from protolanguage to language.

Simulating multiple sequence alignments (MSAs) using probabilistic models of sequence evolution plays an important role in the evaluation of phylogenetic inference tools and is crucial to the development of novel learning-based approaches for phylogenetic reconstruction, for instance, neural networks. These models and the resulting simulated data need to be as realistic as possible to be indicative of the performance of the developed tools on empirical data and to ensure that neural networks trained on simulations perform well on empirical data. Over the years, numerous models of evolution have been published with the goal to represent as faithfully as possible the sequence evolution process and thus simulate empirical-like data. In this study, we simulated DNA and protein MSAs under increasingly complex models of evolution with and without insertion/deletion (indel) events using a state-of-the-art sequence simulator. We assessed their realism by quantifying how accurately supervised learning methods are able to predict whether a given MSA is simulated or empirical. Our results show that we can distinguish between empirical and simulated MSAs with high accuracy using two distinct and independently developed classification approaches across all tested models of sequence evolution. Our findings suggest that the current state-of-the-art models fail to accurately replicate several aspects of empirical MSAs, including site-wise rates as well as amino acid and nucleotide composition.

Anthropology has always had as one of its goals the explanation of human cultural diversity across space and through time. Over the past few years, there has been a growing appreciation among anthropologists that the approaches biologists have developed to reconstruct the evolutionary relationships of species are useful tools for building and explaining patterns of human diversity. One of these methods is cladistics, which is a means of creating testable propositions of heritable continuity—how one thing is related to another in terms of descent. Cladistics has now been applied to a number of cultural data sets. Here we discuss several of these studies, paying particular attention to a series of related papers in which we have applied cladistics to stone tools in an effort to shed light on the early prehistory of North America. Together, these studies demonstrate that cladistics can be fruitfully applied to a range of questions concerning cultural evolutionary processes and events in prehistory.